Probabilistic inference has emerged as a useful language for
describing various aspects of cognition
[1]}, [2]}, [3]}. In
this line of work, people (and other animals) are modeled as if they represent probabilistic
models of their world and use inference in these models to guide
perception and action. While much of the work on biological realizations of probabilistic inference has focused on neural circuits
[1]}, [5]}, single-celled
organisms also face dynamic and uncertain environments that necessitate a
coordinated response by the organism. This situation can be framed in cognitive terms
such as decision-making and inference, and indeed, frameworks from cognitive science
have been applied to the biology of both single
cells and microbial populations
[6]}, [7]}, [8]}, [9]}, [10]}, [11]}. Yet
probabilistic inference is challenging to realize using cellular
biochemistry. In a single cell, for instance, protein
interactions take place stochastically and in parallel, without the
direction of a centralized “conductor” that imposes
sequential order. How can such biochemical substrates support probabilistic
inference?
